Multi-SBI distribution optimization system and method under layered network management based on Gaussian process
A technology of allocation optimization and Gaussian process, applied in transmission systems, digital transmission systems, data exchange networks, etc., can solve problems such as inability to allocate network element supervision
Active Publication Date: 2019-07-09
众邦同力(武汉)技术有限公司
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[0008] The technical problem to be solved by the present invention is to provide a Gaussian process-based multi-SBI distribution optimization system and method under layered network management, to solve the problem that the existing technology in the layered network management system cannot reasonably allocate network elements to be supervised by SBI
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[0030] The present invention will be further described below in conjunction with specific examples and accompanying drawings.
[0031] The present invention provides a multi-SBI distribution optimization system based on Gaussian process layered network management, such as figure 2 As shown, it includes an initialization module, an acquisition module and a distribution module; among them,
[0032]The initialization module is used to take an average distribution method at the beginning, and evenly distribute the network elements to the SBI for processing;
[0033] The collection module includes a data collection module, a data normalization module, a Gaussian regression data completion module and a timed task module; the data collection module is used to collect network element capacity, alarm data, performance data, operation data and Operation time data; the data normalization module is used to classify the collected data according to the network element capacity, divide the...
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The invention provides a multi-SBI (southbound interface) distribution optimizing system under hierarchical network management based on Gaussian process. The multi-SBI distribution optimizing system comprises an initializing module, a collection module and a distribution module, wherein the initializing module is used for averagely distributing network elements to SBI to be processed in the initial phase; the collection module comprises a data collection module, a data normalization module, a Gaussian regression data supplementing module and a fixed-time task module, and is used for collecting the data in the sampling cycle, classifying according to the capacity of network elements, dividing a time window, calculating and quantifying the number of data of each type of network element according to the time window, normalizing and correcting; the distribution module comprises an optimized combination module and an SBI distribution module; the SBI distribution module is used for continuously obtaining the new network element, and sending the obtained network element to the optimized combination module, and the new network element is distributed to the SBI with optimum distribution after calculation. The multi-SBI distribution optimizing system has the advantages that the multi-SBI distribution optimizing under the hierarchical network management can be realized, and the problem of unreasonable distribution of network elements for the SBI supervision of the hierarchical network management system in the prior art is solved.
Description
technical field [0001] The invention relates to the fields of communication and computer, in particular to a multi-SBI allocation optimization system and method under Gaussian process-based layered network management. Background technique [0002] In the management of a network system composed of a large number of network elements, the network management system will adopt a hierarchical management method, that is, multiple EMS (network Element Management Assigned to different upper-layer EMS system management, one EMS will have several SBI (Southbound interface), and the SBI is responsible for managing the connection with the network elements and monitoring the network elements. In this case, which SBI to assign the network element to handle will be a more complicated issue, because the management complexity of different network elements is different, and the data processing scale in different periods is also different; in addition, the network will also Faced with problems...
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IPC IPC(8): H04L12/24
CPCH04L41/0823H04L41/0893
Inventor 何双江
Owner 众邦同力(武汉)技术有限公司